Combining cascade PCA and face shape models for robust registration

3D facial feature point localization is very important to registration. This paper proposes a localization method that is capable of locating 3D facial feature points rapidly while achieving high localization and registration accuracy. There are two contributions of this paper. The first is the introduction of the Cascade PCA which allows the non-occluded and symmetric face models to be normalized quickly while spending more computation on occluded face models. The second is the three face shape models which are used to verify the normalization results produced by Cascade PCA, and localize dozens of feature points at the same time. Experimental results prove the efficiency and accuracy of our method both in localization and registration.